15 citations · 68 across the 34 of their papers we have counts for
6 papers · 1 filter
K-Edit: Language Model Editing with Contextual Knowledge Awareness
Elan Markowitz, Anil Ramakrishna, Ninareh Mehrabi +4
As the world changes, we need to be able to update our models and correct false information without costly retraining. Knowledge-based model editing enables precise modifications t…
Towards Multi-Objective Statistically Fair Federated Learning
Ninareh Mehrabi, Cyprien de Lichy, John McKay +2
Federated Learning (FL) has emerged as a result of data ownership and privacy concerns to prevent data from being shared between multiple parties included in a training procedure.…
Exacerbating Algorithmic Bias through Fairness Attacks
Ninareh Mehrabi, Muhammad Naveed, Fred Morstatter +1
Algorithmic fairness has attracted significant attention in recent years, with many quantitative measures suggested for characterizing the fairness of different machine learning al…
Statistical Equity: A Fairness Classification Objective
Ninareh Mehrabi, Yuzhong Huang, Fred Morstatter
Machine learning systems have been shown to propagate the societal errors of the past. In light of this, a wealth of research focuses on designing solutions that are "fair." Even w…
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena +2
With the widespread use of AI systems and applications in our everyday lives, it is important to take fairness issues into consideration while designing and engineering these types…
DynamicGEM: A Library for Dynamic Graph Embedding Methods
Palash Goyal, Sujit Rokka Chhetri, Ninareh Mehrabi +2
DynamicGEM is an open-source Python library for learning node representations of dynamic graphs. It consists of state-of-the-art algorithms for defining embeddings of nodes whose c…